Big data and analytics (BDA) are gaining momentum, particularly in the practitioner world.
Research linking BDA to improved organizational performance seems scarce and widely …

Despite the importance of data mining techniques to customer relationship management
(CRM), there is a lack of a comprehensive literature review and a classification scheme for it …

Energy prediction models are used in buildings as a performance evaluation engine in
advanced control and optimisation, and in making informed decisions by facility managers …

This paper proposes a method for detecting and classifying ship abnormal behaviour in ship
trajectories. The method involves generating parameter profiles for the ship's trajectory and …

This paper examines churn prediction of customers in the banking sector using a unique
customer-level dataset from a large Brazilian bank. Our main contribution is in exploring this …

Credit card fraud is a serious and growing problem. While predictive models for credit card
fraud detection are in active use in practice, reported studies on the use of data mining …

Data preparation is a process that aims to convert independent (categorical and continuous)
variables into a form appropriate for further analysis. We examine data-preparation …

Background The random forests algorithm is a type of classifier with prominent universality,
a wide application range, and robustness for avoiding overfitting. But there are still some …

Predicting future customer behavior provides key information for efficiently directing
resources at sales and marketing departments. Such information supports planning the …

Random forests (RF) has become a popular technique for classification, prediction, studying
variable importance, variable selection, and outlier detection. There are numerous …